Method and system for artificial intelligence model training using a watermark-enabled kernel for a data processing accelerator

A data processing (DP) accelerator, comprising:

• an interface to receive first data representing a set of training data and to receive a watermark kernel from a host processor;
• and
• a kernel executor to execute the watermark kernel on an artificial intelligence (AI) model, wherein the watermark kernel, when executed, is configured to:
• generate a watermark,
• train the AI model using the set of training data, and
• implant the watermark within the AI model during training of the AI model,
• wherein second data representing the trained AI model having the watermark implanted therein is transmitted to the host processor.

A non-transitory machine-readable medium having instructions stored therein, which when executed by a data processing (DP) accelerator, cause the DP accelerator to perform operations, the operations comprising:

• receiving, at the DP accelerator, first data representing a set of training data from a host processor;
• receiving, at the DP accelerator, a watermark kernel from the host processor;
• executing the watermark kernel within the DP accelerator on an AI model, wherein
• the watermark kernel, when executed, is configured to
• generate a watermark,
• train the AI model using the set of training data, and
• implant the watermark within the AI model during training of the AI model;
• and
• transmitting second data representing the trained AI model having the watermark implanted therein to the host processor.